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Browsing by Author "Geschwind, Daniel"
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Item The Autism Simplex Collection: an international, expertly phenotyped autism sample for genetic and phenotypic analyses(BioMed Central, 2014-05) Buxbaum, Joseph D.; Bolshakova, Nadia; Brownfeld, Jessica M.; Anney, Richard J. L.; Bender, Patrick; Bernier, Raphael; Cook, Edwin H.; Coon, Hilary; Cuccaro, Michael; Freitag, Christine M.; Hallmayer, Joachim; Geschwind, Daniel; Klauck, Sabine M.; Nurnberger, John I.; Oliveira, Guiomar; Pinto, Dalila; Poustka, Fritz; Scherer, Stephen W.; Shih, Andy; Sutcliffe, James S.; Szatmari, Peter; Vicente, Astrid M.; Vieland, Veronica; Gallagher, Louise; Department of Psychiatry, IU School of MedicineBackground There is an urgent need for expanding and enhancing autism spectrum disorder (ASD) samples, in order to better understand causes of ASD. Methods In a unique public-private partnership, 13 sites with extensive experience in both the assessment and diagnosis of ASD embarked on an ambitious, 2-year program to collect samples for genetic and phenotypic research and begin analyses on these samples. The program was called The Autism Simplex Collection (TASC). TASC sample collection began in 2008 and was completed in 2010, and included nine sites from North America and four sites from Western Europe, as well as a centralized Data Coordinating Center. Results Over 1,700 trios are part of this collection, with DNA from transformed cells now available through the National Institute of Mental Health (NIMH). Autism Diagnostic Interview-Revised (ADI-R) and Autism Diagnostic Observation Schedule-Generic (ADOS-G) measures are available for all probands, as are standardized IQ measures, Vineland Adaptive Behavioral Scales (VABS), the Social Responsiveness Scale (SRS), Peabody Picture Vocabulary Test (PPVT), and physical measures (height, weight, and head circumference). At almost every site, additional phenotypic measures were collected, including the Broad Autism Phenotype Questionnaire (BAPQ) and Repetitive Behavior Scale-Revised (RBS-R), as well as the non-word repetition scale, Communication Checklist (Children’s or Adult), and Aberrant Behavior Checklist (ABC). Moreover, for nearly 1,000 trios, the Autism Genome Project Consortium (AGP) has carried out Illumina 1 M SNP genotyping and called copy number variation (CNV) in the samples, with data being made available through the National Institutes of Health (NIH). Whole exome sequencing (WES) has been carried out in over 500 probands, together with ancestry matched controls, and this data is also available through the NIH. Additional WES is being carried out by the Autism Sequencing Consortium (ASC), where the focus is on sequencing complete trios. ASC sequencing for the first 1,000 samples (all from whole-blood DNA) is complete and data will be released in 2014. Data is being made available through NIH databases (database of Genotypes and Phenotypes (dbGaP) and National Database for Autism Research (NDAR)) with DNA released in Dist 11.0. Primary funding for the collection, genotyping, sequencing and distribution of TASC samples was provided by Autism Speaks and the NIH, including the National Institute of Mental Health (NIMH) and the National Human Genetics Research Institute (NHGRI). Conclusions TASC represents an important sample set that leverages expert sites. Similar approaches, leveraging expert sites and ongoing studies, represent an important path towards further enhancing available ASD samples.Item Clinicopathological correlations in behavioural variant frontotemporal dementia(Oxford University Press, 2017-12-01) Perry, David C.; Brown, Jesse A.; Possin, Katherine L.; Datta, Samir; Trujillo, Andrew; Radke, Anneliese; Karydas, Anna; Kornak, John; Sias, Ana C.; Rabinovici, Gil D.; Gorno-Tempini, Maria Luisa; Boxer, Adam L.; May, Mary De; Rankin, Katherine P.; Sturm, Virginia E.; Lee, Suzee E.; Matthews, Brandy R.; Kao, Aimee W.; Vossel, Keith A.; Tartaglia, Maria Carmela; Miller, Zachary A.; Seo, Sang Won; Sidhu, Manu; Gaus, Stephanie E.; Nana, Alissa L.; Vargas, Jose Norberto S.; Hwang, Ji-Hye L.; Ossenkoppele, Rik; Brown, Alainna B.; Huang, Eric J.; Coppola, Giovanni; Rosen, Howard J.; Geschwind, Daniel; Trojanowski, John Q.; Grinberg, Lea T.; Kramer, Joel H.; Miller, Bruce L.; Seely, William W.; Neurology, School of MedicineAccurately predicting the underlying neuropathological diagnosis in patients with behavioural variant frontotemporal dementia (bvFTD) poses a daunting challenge for clinicians but will be critical for the success of disease-modifying therapies. We sought to improve pathological prediction by exploring clinicopathological correlations in a large bvFTD cohort. Among 438 patients in whom bvFTD was either the top or an alternative possible clinical diagnosis, 117 had available autopsy data, including 98 with a primary pathological diagnosis of frontotemporal lobar degeneration (FTLD), 15 with Alzheimer's disease, and four with amyotrophic lateral sclerosis who lacked neurodegenerative disease-related pathology outside of the motor system. Patients with FTLD were distributed between FTLD-tau (34 patients: 10 corticobasal degeneration, nine progressive supranuclear palsy, eight Pick's disease, three frontotemporal dementia with parkinsonism associated with chromosome 17, three unclassifiable tauopathy, and one argyrophilic grain disease); FTLD-TDP (55 patients: nine type A including one with motor neuron disease, 27 type B including 21 with motor neuron disease, eight type C with right temporal lobe presentations, and 11 unclassifiable including eight with motor neuron disease), FTLD-FUS (eight patients), and one patient with FTLD-ubiquitin proteasome system positive inclusions (FTLD-UPS) that stained negatively for tau, TDP-43, and FUS. Alzheimer's disease was uncommon (6%) among patients whose only top diagnosis during follow-up was bvFTD. Seventy-nine per cent of FTLD-tau, 86% of FTLD-TDP, and 88% of FTLD-FUS met at least 'possible' bvFTD diagnostic criteria at first presentation. The frequency of the six core bvFTD diagnostic features was similar in FTLD-tau and FTLD-TDP, suggesting that these features alone cannot be used to separate patients by major molecular class. Voxel-based morphometry revealed that nearly all pathological subgroups and even individual patients share atrophy in anterior cingulate, frontoinsula, striatum, and amygdala, indicating that degeneration of these regions is intimately linked to the behavioural syndrome produced by these diverse aetiologies. In addition to these unifying features, symptom profiles also differed among pathological subtypes, suggesting distinct anatomical vulnerabilities and informing a clinician's prediction of pathological diagnosis. Data-driven classification into one of the 10 most common pathological diagnoses was most accurate (up to 60.2%) when using a combination of known predictive factors (genetic mutations, motor features, or striking atrophy patterns) and the results of a discriminant function analysis that incorporated clinical, neuroimaging, and neuropsychological data.Item Temporal order of clinical and biomarker changes in familial frontotemporal dementia(Springer Nature, 2022) Staffaroni, Adam M.; Quintana, Melanie; Wendelberger, Barbara; Heuer, Hilary W.; Russell, Lucy L.; Cobigo, Yann; Wolf, Amy; Goh, Sheng-Yang Matt; Petrucelli, Leonard; Gendron, Tania F.; Heller, Carolin; Clark, Annie L.; Taylor, Jack Carson; Wise, Amy; Ong, Elise; Forsberg, Leah; Brushaber, Danielle; Rojas, Julio C.; VandeVrede, Lawren; Ljubenkov, Peter; Kramer, Joel; Casaletto, Kaitlin B.; Appleby, Brian; Bordelon, Yvette; Botha, Hugo; Dickerson, Bradford C.; Domoto-Reilly, Kimiko; Fields, Julie A.; Foroud, Tatiana; Gavrilova, Ralitza; Geschwind, Daniel; Ghoshal, Nupur; Goldman, Jill; Graff-Radford, Jonathon; Graff-Radford, Neill; Grossman, Murray; Hall, Matthew G. H.; Hsiung, Ging-Yuek; Huey, Edward D.; Irwin, David; Jones, David T.; Kantarci, Kejal; Kaufer, Daniel; Knopman, David; Kremers, Walter; Lago, Argentina Lario; Lapid, Maria I.; Litvan, Irene; Lucente, Diane; Mackenzie, Ian R.; Mendez, Mario F.; Mester, Carly; Miller, Bruce L.; Onyike, Chiadi U.; Rademakers, Rosa; Ramanan, Vijay K.; Ramos, Eliana Marisa; Rao, Meghana; Rascovsky, Katya; Rankin, Katherine P.; Roberson, Erik D.; Savica, Rodolfo; Tartaglia, M. Carmela; Weintraub, Sandra; Wong, Bonnie; Cash, David M.; Bouzigues, Arabella; Swift, Imogen J.; Peakman, Georgia; Bocchetta, Martina; Todd, Emily G.; Convery, Rhian S.; Rowe, James B.; Borroni, Barbara; Galimberti, Daniela; Tiraboschi, Pietro; Masellis, Mario; Finger, Elizabeth; van Swieten, John C.; Seelaar, Harro; Jiskoot, Lize C.; Sorbi, Sandro; Butler, Chris R.; Graff, Caroline; Gerhard, Alexander; Langheinrich, Tobias; Laforce, Robert; Sanchez-Valle, Raquel; de Mendonça, Alexandre; Moreno, Fermin; Synofzik, Matthis; Vandenberghe, Rik; Ducharme, Simon; Le Ber, Isabelle; Levin, Johannes; Danek, Adrian; Otto, Markus; Pasquier, Florence; Santana, Isabel; Kornak, John; Boeve, Bradley F.; Rosen, Howard J.; Rohrer, Jonathan D.; Boxer, Adam L.; Frontotemporal Dementia Prevention Initiative (FPI) Investigators; Medicine, School of MedicineUnlike familial Alzheimer’s disease, we have been unable to accurately predict symptom onset in presymptomatic familial frontotemporal dementia (f-FTD) mutation carriers, which is a major hurdle to designing disease prevention trials. We developed multimodal models for f-FTD disease progression and estimated clinical trial sample sizes in C9orf72, GRN, and MAPT mutation carriers. Models included longitudinal clinical and neuropsychological scores, regional brain volumes, and plasma neurofilament light chain (NfL) in 796 carriers and 412 non-carrier controls. We found that the temporal ordering of clinical and biomarker progression differed by genotype. In prevention-trial simulations employing model-based patient selection, atrophy and NfL were the best endpoints, whereas clinical measures were potential endpoints in early symptomatic trials. F-FTD prevention trials are feasible but will likely require global recruitment efforts. These disease progression models will facilitate the planning of f-FTD clinical trials, including the selection of optimal endpoints and enrollment criteria to maximize power to detect treatment effects.